Solution Architect AI Platforms

As a Solution Architect at Codvo, you will play a crucial role in bridging complex business challenges with the innovative capabilities of our AI platform. Your responsibilities will include collaborating with clients, designing end-to-end solutions, architecting core intelligence, providing technical leadership, leading proof of concept projects, collaborating cross-functionally, guiding implementation and user acceptance testing, and continuously learning about advancements in AI landscape. **Key Responsibilities:** - Collaborate closely with enterprise clients to understand their business processes, pain points, data ecosystems, and strategic goals. - Design end-to-end solutions by mapping client requirements to our platform's offerings like Knowledge Hubs, Conversational AI, Real-time Insights, and Agentic Automation. - Architect the core intelligence for client solutions including designing client-specific ontologies and defining Model Context Protocols (MCPs). - Serve as the deep technical expert on the platform for clients and internal teams, providing guidance on data integration, RAG implementation, and agentic automation. - Lead the technical design and development of Proof of Concept projects to showcase the value of our solutions for specific client use cases. - Work closely with Engineering and Product teams to ensure proposed solutions are feasible, scalable, and align with the platform's core principles. - Provide architectural oversight and technical guidance during implementation and User Acceptance Testing phases of client projects. - Maintain a deep understanding of the rapidly evolving AI landscape and integrate new knowledge into solution designs. **Required Qualifications & Skills:** - 8+ years of experience in Solution Architecture, Enterprise Architecture, or senior-level Software Engineering, with 3+ years in a client-facing role. - Proven ability to design complex, distributed, and scalable software systems with expertise in microservices, event-driven architecture, and MCP-first design principles. - Strong foundational knowledge of modern AI concepts, including LLMs, RAG, and vector databases. - Hands-on experience in designing data pipelines and integrating with diverse data sources. - Experience in architecting solutions on major cloud platforms like AWS, Azure, or GCP. - Proficiency in Python, familiarity with containerization (Docker), and orchestration (Kubernetes). - Exceptional verbal and written communication skills to explain technical concepts to diverse audiences. Preferred Qualifications (Nice to Have): - Direct experience with agentic AI frameworks, semantic web technologies, and graph databases. - Familiarity with Model Context Protocol or similar advanced agentic architectures. - Experience with observability stacks like OpenTelemetry and designing enterprise software platforms. - Knowledge of enterprise security patterns and identity management systems.,